TY - GEN
T1 - Design of a brain-controlled robot arm system based on upper-limb movement imagery
AU - Jeong, Ji Hoon
AU - Kim, Keun Tae
AU - Yun, Yong Deok
AU - Lee, Seong Whan
N1 - Funding Information:
This work was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (No.2017-0-00432, Development of non-invasive integrated BCI SW platform to control home appliances and external devices by user's thought via AR/VR interface).
Publisher Copyright:
© 2018 IEEE.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/3/9
Y1 - 2018/3/9
N2 - 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.
AB - 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.
KW - a robot arm
KW - brain machine interface
KW - electro-encephalography
KW - upper-limb movement imagery
UR - http://www.scopus.com/inward/record.url?scp=85050808755&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050808755&partnerID=8YFLogxK
U2 - 10.1109/IWW-BCI.2018.8311514
DO - 10.1109/IWW-BCI.2018.8311514
M3 - Conference contribution
AN - SCOPUS:85050808755
T3 - 2018 6th International Conference on Brain-Computer Interface, BCI 2018
SP - 1
EP - 3
BT - 2018 6th International Conference on Brain-Computer Interface, BCI 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Brain-Computer Interface, BCI 2018
Y2 - 15 January 2018 through 17 January 2018
ER -