Name
Abstract | ||
|---|---|---|
Motor synergies have been investigated since the 1980s as a simplifying representation of motor control by the nervous system. This way of representing finger positional data is in particular useful to represent the kinematics of the human hand. Whereas, so far, the focus has been on kinematic synergies, that is common patterns in the motion of the hand and fingers, we hereby also investigate their force aspects, evaluated through surface electromyography (sEMG). We especially show that force-related motor synergies exist, i.e. that muscle activation during grasping, as described by the sEMG signal, can be grouped synergistically; that these synergies are largely comparable to one another across human subjects notwithstanding the disturbances and inaccuracies typical of sEMG; and that they are physiologically feasible representations of muscular activity during grasping. Potential applications of this work include force control of mechanical hands, especially when many degrees of freedom must be simultaneously controlled. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/s00422-013-0548-4 | Biological Cybernetics |
Keywords | Field | DocType |
Rehabilitation robotics,Grasping,Electromyography | Kinematics,Electromyography,Motor control,Muscle activation,Human–computer interaction,Artificial intelligence,Rehabilitation robotics,Engineering,Machine learning | Journal |
Volume | Issue | ISSN |
107 | 2 | 1432-0770 |
Citations | PageRank | References |
7 | 0.79 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Claudio Castellini | 1 | 448 | 33.56 |
| P. Patrick Van Der Smagt | 2 | 274 | 35.19 |