Name
Abstract | ||
|---|---|---|
Surgical robots are increasingly common, yet routine tasks such as tissue grasping remain potentially harmful with high occurrences of tissue crush injury due to the lack of force feedback from the grasper. This work aims to investigate whether a blended shared control framework which utilizes real-time identification of the object being grasped as part of the feedback may help address the prevalence of tissue crush injury in robotic surgeries. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s11548-018-1745-3 | Int. J. Computer Assisted Radiology and Surgery |
Keywords | Field | DocType |
Shared control,Robotic surgery,Tissue identification,Tissue crush injury | Online identification,Computer vision,Robotic surgery,Human–computer interaction,Artificial intelligence,Robot,Medicine,Haptic technology,Crush injury | Journal |
Volume | Issue | ISSN |
13 | 6 | 1861-6410 |
Citations | PageRank | References |
3 | 0.47 | 8 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Trevor K. Stephens | 1 | 9 | 1.34 |
| Nathan J. Kong | 2 | 5 | 0.94 |
| Rodney Dockter | 3 | 7 | 1.70 |
| John J. O'Neill | 4 | 4 | 1.17 |
| Robert M. Sweet | 5 | 11 | 6.45 |
| Timothy M Kowalewski | 6 | 18 | 6.48 |