Abstract
This paper presents a prototype for a brain-controlled robot arm system using a variety of upper-limb movement imagery. To do that, we have designed the experimental environment based on brain signals. The experimental system architecture was modularized into three main components: BMI, network, and control parts. Six subjects participated in our experiments. The subject performed various upper-limb actual movement and imagery task. Each task consisted of three different movement/imagery: Arm reaching tasks, hand grasping tasks, and wrist twisting tasks. We confirmed the classification accuracies are 22.65%, 50.79%, and 54.44%, respectively. Moreover, we will demonstrate that brain-controlled robot arm system can achieve a high-level task in multi-dimensional space.
| Original language | English |
|---|---|
| Title of host publication | 2018 6th International Conference on Brain-Computer Interface, BCI 2018 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1-3 |
| Number of pages | 3 |
| Volume | 2018-January |
| ISBN (Electronic) | 9781538625743 |
| DOIs | |
| Publication status | Published - 2018 Mar 9 |
| Event | 6th International Conference on Brain-Computer Interface, BCI 2018 - GangWon, Korea, Republic of Duration: 2018 Jan 15 → 2018 Jan 17 |
Other
| Other | 6th International Conference on Brain-Computer Interface, BCI 2018 |
|---|---|
| Country | Korea, Republic of |
| City | GangWon |
| Period | 18/1/15 → 18/1/17 |
Keywords
- a robot arm
- brain machine interface
- electro-encephalography
- upper-limb movement imagery
ASJC Scopus subject areas
- Artificial Intelligence
- Human-Computer Interaction
- Behavioral Neuroscience