TY - JOUR
T1 - Robot motion control using the emotiv EPOC EEG system
AU - Dewangga, Sandy Akbar
AU - Tjandrasa, Handayani
AU - Herumurti, Darlis
N1 - Publisher Copyright:
© 2018 Institute of Advanced Engineering and Science. All rights reserved.
PY - 2018/6
Y1 - 2018/6
N2 - Brain-computer interfaces have been explored for years with the intent of using human thoughts to control mechanical system. By capturing the transmission of signals directly from the human brain or electroencephalogram (EEG), human thoughts can be made as motion commands to the robot. This paper presents a prototype for an electroencephalogram (EEG) based brain-actuated robot control system using mental commands. In this study, Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) method were combined to establish the best model. Dataset containing features of EEG signals were obtained from the subject non-invasively using Emotiv EPOC headset. The best model was then used by Brain-Computer Interface (BCI) to classify the EEG signals into robot motion commands to control the robot directly. The result of the classification gave the average accuracy of 69.06%.
AB - Brain-computer interfaces have been explored for years with the intent of using human thoughts to control mechanical system. By capturing the transmission of signals directly from the human brain or electroencephalogram (EEG), human thoughts can be made as motion commands to the robot. This paper presents a prototype for an electroencephalogram (EEG) based brain-actuated robot control system using mental commands. In this study, Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) method were combined to establish the best model. Dataset containing features of EEG signals were obtained from the subject non-invasively using Emotiv EPOC headset. The best model was then used by Brain-Computer Interface (BCI) to classify the EEG signals into robot motion commands to control the robot directly. The result of the classification gave the average accuracy of 69.06%.
KW - Brain-computer interface
KW - Electroencephalogram (EEG)
KW - Emotiv epoc
KW - Linear discriminant analysis
KW - Support vector machine
UR - http://www.scopus.com/inward/record.url?scp=85049914631&partnerID=8YFLogxK
U2 - 10.11591/eei.v7i2.678
DO - 10.11591/eei.v7i2.678
M3 - Article
AN - SCOPUS:85049914631
SN - 2089-3191
VL - 7
SP - 279
EP - 285
JO - Bulletin of Electrical Engineering and Informatics
JF - Bulletin of Electrical Engineering and Informatics
IS - 2
ER -