Name
Title | ||
|---|---|---|
Pattern recognition of electromyography signals based on novel time domain features for amputees' limb motion classification. |
Abstract | ||
|---|---|---|
•This study proposed three new time domain (TD) features for EMG Pattern recognition (EMG-PR).•The performances of these features were examined using four performance metrics.•The results showed that the newly proposed features outperform the previously used TD features.•These features might improve the control performance of EMG-PR based prostheses. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.compeleceng.2017.04.003 | Computers & Electrical Engineering |
Keywords | Field | DocType |
Rehabilitation robotics,Electromyography,Time domain features,Myoelectric prostheses,Pattern recognition,Upper-limb amputees | Time domain,Residual,Upper limb,Pattern recognition,Computer science,Electromyography,Feature extraction,Artificial intelligence,Rehabilitation robotics | Journal |
Volume | ISSN | Citations |
67 | 0045-7906 | 25 |
PageRank | References | Authors |
1.31 | 7 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| O. W. Samuel | 1 | 161 | 22.87 |
| Hui Zhou | 2 | 41 | 14.35 |
| Xiangxin Li | 3 | 45 | 8.34 |
| Hui Wang | 4 | 291 | 85.17 |
| Haoshi Zhang | 5 | 28 | 2.81 |
| Arun Kumar | 6 | 1427 | 132.32 |
| Guanglin Li | 7 | 314 | 57.23 |