@inproceedings{cbbd511c1abe4b4cbfe092943b35f90a,
title = "Brain Computer Interface Using Motor Imagery and Facial Expressions to Control A Mobile Robot",
abstract = "The paper presents a study on brain computer interface (BCI) using motor imagery (MI) and facial expressions to control a mobile robot. Traditionally, only MI signals are used in BCI applications. In this paper a hybrid approach of using both MI and facial expression stimulations for BCI is proposed. Electroencephalography (EEG) signals were acquired using a sensor system and processed for several MI and facial expressions to extract characteristic features. The features were used to train support vector machine (SVM) based classifiers and the trained classifiers were used to recognize test signals for correct identification of MI and facial expressions. A system was developed to implement the BCI using MI and facial expressions to control a mobile robot. Results of robot control using MI and facial expressions, individually and together are presented for comparison. The combined features from MI and facial expression stimulations were found to give better performance than MI and facial expressions used individually.",
keywords = "Brain computer interface, common spatial patterns, electroencephalography, facial expression, independent component analysis, motor imagery, power spectral Density, support vector machine",
author = "James Kuffuor and Biswanath Samanta",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Southeastcon, Southeastcon 2018 ; Conference date: 19-04-2018 Through 22-04-2018",
year = "2018",
month = oct,
day = "1",
doi = "10.1109/SECON.2018.8479052",
language = "English",
series = "Conference Proceedings - IEEE SOUTHEASTCON",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Southeastcon 2018",
address = "United States",
}