Name
Title | ||
|---|---|---|
DESIGN AND DEVELOPMENT OF HUMAN COMPUTER INTERFACE USING ELECTROOCULOGRAM WITH DEEP LEARNING |
Abstract | ||
|---|---|---|
•Electrooculogram based Human computer Interface is designed using deep learning.•Hibert Huang Transform based features are extracted.•Over 91 % accuracy is achieved for all cases using Pattern Recognition Neural Network classifier. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.artmed.2019.101765 | Artificial Intelligence in Medicine |
Keywords | Field | DocType |
Electrooculogram (EOG),Band Power (BP),Human Computer Interface (HCI),Amyotrophic lateral sclerosis (ALS),Pattern Recognition Neural Network (PRNN) | Age groups,Computer science,Feature extraction,Eye movement,Human–computer interaction,Artificial intelligence,Deep learning,Artificial neural network,Hilbert–Huang transform | Journal |
Volume | ISSN | Citations |
102 | 0933-3657 | 3 |
PageRank | References | Authors |
0.40 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Geer Teng | 1 | 3 | 0.40 |
| Yue He | 2 | 105 | 16.62 |
| Hengjun Zhao | 3 | 3 | 0.40 |
| Dunhu Liu | 4 | 3 | 0.40 |
| Jin Xiao | 5 | 80 | 8.89 |
| S. Ramkumar | 6 | 18 | 3.46 |