Name
Title | ||
|---|---|---|
Comparison Of Hand And Forearm Muscle Pairs In Controlling Of A Novel Myoelectric Interface |
Abstract | ||
|---|---|---|
With commercial prosthetic hands, executing some everyday movements, for example, concurrent grasp and bending of the wrist to pick up an object from a high shelf, is very challenging. We hypothesised that after the loss of the hand, the flexibility of the nervous system enables prosthesis users to bypass the innate biomechanical constraints on upper-limb muscles and joints. We show that users are able to learn to operate a myoelectric-controlled interface by flexibly contracting pairs of hand and forearm muscles. The use of these novel activity patterns can have a transformative effect on the control of future prosthetic hands. |
Year | Venue | Field |
|---|---|---|
2016 | 2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC) | Prosthesis,GRASP,Wrist,Visualization,Computer science,Simulation,Human–computer interaction,Forearm,Artificial intelligence,Forearm muscle,Machine learning |
DocType | ISSN | Citations |
Conference | 1062-922X | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jessica Barnes | 1 | 0 | 0.68 |
| Matthew Dyson | 2 | 0 | 2.70 |
| Kianoush Nazarpour | 3 | 75 | 19.08 |