Name
Abstract | ||
|---|---|---|
•End-to-end neural network model for classifying motor imagery EEG signals.•Using 1-D CNN layers to learn temporal and spatial filters for feature extraction.•Application of transfer learning to calibrate the model for individual subjects.•Analysis of the temporal and spatial filters learned by the model. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.eswa.2018.08.031 | Expert Systems with Applications |
Keywords | Field | DocType |
Deep learning (DL),Electroencephalogram (EEG),Motor imagery (MI),Convolutional neural networks (CNNs),Brain computer interface (BCI),Stroke rehabilitation | Dimensionality reduction,Convolutional neural network,Computer science,Transfer of learning,Robustness (computer science),Feature extraction,Artificial intelligence,Deep learning,Classifier (linguistics),Machine learning,Motor imagery | Journal |
Volume | ISSN | Citations |
114 | 0957-4174 | 13 |
PageRank | References | Authors |
0.58 | 15 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hauke Dose | 1 | 14 | 0.98 |
| Jakob S. Møller | 2 | 17 | 1.73 |
| Helle K Iversen | 3 | 18 | 3.56 |
| Sadasivan Puthusserypady | 4 | 181 | 27.49 |