Simple and Fast Compensation of sEMG Interface Rotation for Robust Hand Motion Recognition
Minjae Kim, Keehoon Kim, Wan Kyun Chung
- Year
- 2018
- Citations
- 41
Abstract
Surface electromyography (sEMG) measurements have demonstrated the potential to recognize complex hand motions. In addition, sEMG enables natural recognition without disturbing movements, and thus, can be used in various fields such as teleoperation, assistant robots, and prosthetic hands. However, sEMG signals highly depend on electrode placements due to the complex muscle structures. A shift of the electrode can lead to inconsistent signal measurement. Thus, sEMG-based recognition is not practical for applications that require long-term and repeated usage. This paper proposes compensation of sEMG interface rotation for robust motion recognition. Once the relationship between sEMG signals and motions is trained, additional training for different electrode configurations is not necessary for a band-type interface. The proposed process is simple and fast. The interface rotation can be compensated for by performing only a single motion for approximately 2 s. The single motion for compensation is dependent on the muscle properties of the user. Generally, ulnar deviation may work. To demonstrate the proposed compensation, recognition of five hand motions is conducted. The experimental results indicate that the proposed compensation can cover the overall range of rotation. In addition, the proposed compensation is validated with a transradial amputee.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002